An ever-growing body of evidence suggests that climate change is already impacting human and natural systems around the world. Global environmental assessments assessing this evidence, for example by the Intergovernmental Panel on Climate Change (IPCC) 1 , face increasing challenges to appraise an exponentially growing literature 2 and diverse approaches to climate change attribution. Here we use the language representation model BERT to identify and classify studies on observed climate impacts, producing a machine-learning-assisted evidence map which provides the most comprehensive picture of the literature to date. We identify 100,724 (62,950 − 162,838) publications covering a broad range of impacts in human and natural systems across all continents. By combining our spatially resolved database with human-attributable changes in temperature and precipitation on the grid cell level, we infer that attributable climate change impacts may be occurring in regions encompassing 85% (80%) of the world's population (land area). Our results also reveal a substantial 'attribution gap' as robust evidence for attributable impacts is twice as prevalent in high income compared to low income countries. While substantial gaps remain on con dently establishing attributable climate impacts at the regional and sectoral level, our unique database illustrates the broad extent to which anthropogenic climate change may already be impacting natural systems and societies across the globe. MainThere is overwhelming evidence that the impacts of climate change are already being observed in human and natural systems 3 . These effects are emerging in a range of different systems and at different scales, covering a broad range of research elds from glaciology to agricultural science, and marine biology to migration and con ict research 1 . The evidence base for observed climate impacts is expanding 4 , and the wider climate literature is growing exponentially 5,6 . Systematic reviews and systematic maps offer structured ways to collectively identify and describe this evidence while maintaining transparency, attempting to ensure comprehensiveness and reduce bias 7 . However, their scope is often con ned to very speci c questions covering no more than dozens to hundreds of studies.In the climate science community, evidence-based assessments of observed climate change impacts are performed by the Intergovernmental Panel on Climate Change (IPCC) 1 . Since the rst Assessment Report (AR) of the IPCC in 1990, we estimate that the number of studies relevant to observed climate impacts published per year has increased by more than two orders of magnitude (Fig. 1a). Since the third AR, published in 2001, the number has increased ten-fold. This exponential growth in peer-reviewed scienti c publications on climate change 5,6 is already pushing manual expert assessments to their limits. To address this issue, recent work has investigated ways to handle big literature in sustainability science by scaling systematic review and map methods to large bodies ...

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Anthropogenic climate change is affecting agriculture and crop production. The responses of horticultural and agricultural systems to changing climatic conditions can be non-linear and at times counter-intuitive. Depending on the characteristics of the system, the actual impact can arise as a result of a combination of climate hazards or compound events. Here, we show that compound events can lead to increased risk of frost damage for apple fruit trees in Germany in a 2°C warmer world of up to 10% relative to present day. Although the absolute number of frost days is declining, warmer winters also lead to earlier blossom of fruit trees, which in turn can lead to regionally dependent increased risks of the occurrence of frost days after apple blossom. In southern Germany, warmer winters may also lead to an increase in years in which apple yield is negatively affected by a lack of sufficient amount of cold days to trigger the seasonal response of the trees. Our results show how cropping system responses to seasonal climate can lead to unexpected effects of increased risk of frost damage as a result of warmer winters. An improved understanding of ecosystem responses to changes in climate signals is important to fully assess the impacts of climate change.

Transformation pathways for the land sector in line with the Paris Agreement depend on the assumption of globally implemented greenhouse gas (GHG) emission pricing, and in some cases also on inclusive socio-economic development and sustainable land-use practices. In such pathways, the majority of GHG emission reductions in the land system is expected to come from low- and middle-income countries, which currently account for a large share of emissions from agriculture, forestry and other land use (AFOLU). However, in low- and middle-income countries the economic, financial and institutional barriers for such transformative changes are high. Here, we show that if sustainable development in the land sector remained highly unequal and limited to high-income countries only, global AFOLU emissions would remain substantial throughout the 21st century. Our model-based projections highlight that overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement. While also a scenario purely based on either global GHG emission pricing or on inclusive socio-economic development would achieve the stringent emissions reductions required, only the latter ensures major co-benefits for other Sustainable Development Goals, especially in low- and middle-income regions.